Triple

T7585522
Position Surface form Disambiguated ID Type / Status
Subject Uniformed EMS Officers Union E179602 entity
Predicate abbreviation P43 FINISHED
Object UEMSO
UEMSO is the acronym for the Uniformed EMS Officers Union, a labor organization representing uniformed emergency medical services officers.
E674501 NE FINISHED

How this triple was built (4 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: UEMSO | Statement: [Uniformed EMS Officers Union, abbreviation, UEMSO]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: UEMSO
Context triple: [Uniformed EMS Officers Union, abbreviation, UEMSO]
  • A. UMS
    UMS is the public university system that oversees multiple campuses and educational institutions across the state of Maine.
  • B. UMS
    UMS is a public university system in the U.S. state of Missouri that oversees multiple campuses, including the University of Missouri in Columbia.
  • C. UMI
    UMI is the three-letter ISO 3166-1 alpha-3 country code assigned to Kingman Reef, an uninhabited U.S. territory in the central Pacific Ocean.
  • D. USEU
    USEU is the official diplomatic mission representing the United States government to the institutions of the European Union in Brussels.
  • E. UMES
    UMES is a public historically Black land-grant university located in Princess Anne, Maryland, known for its programs in agriculture, marine and environmental science, and hospitality management.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: UEMSO
Triple: [Uniformed EMS Officers Union, abbreviation, UEMSO]
Generated description
UEMSO is the acronym for the Uniformed EMS Officers Union, a labor organization representing uniformed emergency medical services officers.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: UEMSO
Target entity description: UEMSO is the acronym for the Uniformed EMS Officers Union, a labor organization representing uniformed emergency medical services officers.
  • A. UMS
    UMS is the public university system that oversees multiple campuses and educational institutions across the state of Maine.
  • B. UMS
    UMS is a public university system in the U.S. state of Missouri that oversees multiple campuses, including the University of Missouri in Columbia.
  • C. UMI
    UMI is the three-letter ISO 3166-1 alpha-3 country code assigned to Kingman Reef, an uninhabited U.S. territory in the central Pacific Ocean.
  • D. USEU
    USEU is the official diplomatic mission representing the United States government to the institutions of the European Union in Brussels.
  • E. UMES
    UMES is a public historically Black land-grant university located in Princess Anne, Maryland, known for its programs in agriculture, marine and environmental science, and hospitality management.
  • F. None of above. chosen

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69c69f335248819093c1006f30513708 completed March 27, 2026, 3:16 p.m.
NER Named-entity recognition batch_69c6f995c8a8819089817bd679640017 completed March 27, 2026, 9:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69c861812e08819097fd14fe2b8fee13 completed March 28, 2026, 11:17 p.m.
NEDg Description generation batch_69c862466fd481908ea5772e76a88d95 completed March 28, 2026, 11:20 p.m.
NED2 Entity disambiguation (via description) batch_69c862cae0448190859a07db338e1de7 completed March 28, 2026, 11:22 p.m.
Created at: March 27, 2026, 3:52 p.m.